基于赫斯特指数和变异函数的手腕和前臂动觉运动意象范式表征

2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC) Pub Date : 2020-10-11 DOI:10.1109/SMC42975.2020.9282888

A. Mosqueda-Herrera, D. Martinez-Peon, L. Gomez-Sanchez, M. I. Ramirez-Sosa, S. Delfin-Prieto, F. Benavides-Bravo

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引用次数: 0

摘要

动觉运动意象(MKI)已被证明是脑机接口(BCI)的一个强大范例。本文采用赫斯特指数和变异函数对右臂腕部和前臂三个任务的KMI范式进行了表征，然后将信号映射到源空间中。结果显示，KMI前旋/后旋(PS)的平均持续性为0.76±0.07,KMI屈伸(PS)的平均持续性为0.82±0.05。(FE)，而KMI外展-内收(AA)则为0.90±0.02。我们发现三个KMI任务之间存在显著差异，这对BCI的多模式命令有用。

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Characterization of Kinesthetic Motor Imagery paradigm for wrist and forearm using an algorithm based on the Hurst Exponent and Variogram

Kinesthetic Motor Imagery (MKI) has been demonstrated to be a robust paradigm for Brain-Computer Interfaces (BCI). In this paper we present the characterization of KMI paradigm of three tasks of wrist and forearm of the right arm using Hurst exponent and variogram, preceding for ICA to map signals into source space. The results show high persistency an average of 0.76 ± 0.07 for KMI Pronation/Supination (PS), 0.82 ± 0.05 for KMI Flexion-Extension). (FE), and 0.90 ± 0.02 for KMI Abduction-Adduction (AA We found a significant difference between the three KMI tasks, useful for multimodal command in BCI.

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2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

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